Handwriting recognition systems on devices such as Tablet PC's or Pocket PC's employ a machine learning model such as a neural network. Achieving good “walkup accuracy” for the large variety of writing styles requires the collection of handwriting samples from many individuals with a large variety handwriting styles. The samples in turn are used to train a handwriting recognizer. Such a recognizer will perform well for popular styles, but less well for less common or unusual handwriting styles which may frequently require the user to make corrections to the recognition result.